varshantdhar

ALAML

Active Learning Automated Machine Learning

Cache-Sim

A Cache Simulator - Project as a part of Introduction to Computer Systems (Fall 2016) - Code in cachelab.c & csim.c

CausalConv

Temporal Convolutions with WeightNorm, mixed dilations

Consensus

Building a website for discussion & opinions on the discourse of the world.

ConvAttention

Marrying Convolution and Attention - https://arxiv.org/abs/2106.04803

Databases-SQL-Java-

Projects from CMSC 23500

ml-scratch

Developing Deep Learning models from scratch to better understand the end-to-end process.

spatio-temporal-covid-19

Exploit a flexible Bayesian nonparametric covariance regression framework to map these location-specific COVID incidences onto a lower-dimensional subspace. Use Factor analysis models to exploit the high rate of spatial and temporal redundancy in the data

TimeGAN-PyTorch

Time Series Generative Adversarial Network implementation in PyTorch

varshantdhar.github.io

Paper reading notes on deep learning and machine learning

varshantdhar/TimeGAN-PyTorch

Time Series Generative Adversarial Network implementation in PyTorch

varshantdhar/ConvAttention

Marrying Convolution and Attention - https://arxiv.org/abs/2106.04803

varshantdhar/spatio-temporal-covid-19

Exploit a flexible Bayesian nonparametric covariance regression framework to map these location-specific COVID incidences onto a lower-dimensional subspace. Use Factor analysis models to exploit the high rate of spatial and temporal redundancy in the data

varshantdhar/ALAML

Active Learning Automated Machine Learning

varshantdhar/Cache-Sim

A Cache Simulator - Project as a part of Introduction to Computer Systems (Fall 2016) - Code in cachelab.c & csim.c

varshantdhar/CausalConv

Temporal Convolutions with WeightNorm, mixed dilations

varshantdhar/Consensus

Building a website for discussion & opinions on the discourse of the world.

varshantdhar/Databases-SQL-Java-

Projects from CMSC 23500

varshantdhar/ml-scratch

Developing Deep Learning models from scratch to better understand the end-to-end process.

varshantdhar/varshantdhar.github.io

Paper reading notes on deep learning and machine learning

varshantdhar/DSaPP_RA_Project

This repository includes an exercise for aspiring DSaPP volunteers and research assistants to complete

varshantdhar/GMM

Variational Inference in Gaussian Mixture Model

varshantdhar/HMM-Parts-of-Speech

HMM for Parts of Speech

varshantdhar/Machine-Learning

Machine Learning Projects worked on in Spring 2018 while taking CMSC 25025

varshantdhar/madrid-airbnb-pricing-predictions

Random Forest Model to predict AirBnb prices based in Madrid

varshantdhar/matching-tool

Integrating HMIS and criminal-justice data

varshantdhar/MyShell

Command Line Interpreter - Project as a part of Introduction to Computer Systems (Fall 2016) - Code in myshell.c

varshantdhar/NBA-Projections

Ranking regression algorithm to predict the counting stats for 60 young NBA players over the next three seasons. Algorithm employs FiveThirtyEight's CARMELO projections and derives statistics from basketball-reference.com

varshantdhar/portfolio-rebalance

varshantdhar/RayTracer

RayTracer project worked on in Winter 2016 as a part of CMSC 152 - Introduction to Computer Science II (Data Structures and Algorithms)

varshantdhar/Reading_Papers

Paper reading notes on deep learning and machine learning

varshantdhar/reedsolomon

varshantdhar/rl_nonparametric_reduced_action_space

Using nonparametric models to reduce the action space for observed states. Optimizes Deep Q-Learning to learn the optimal policy.

varshantdhar/skills-ml

Data Processing and Machine learning methods for the Open Skills Project